Pelagic calcium carbonate production and shallow dissolution in the North Pacific Ocean

Planktonic calcifying organisms play a key role in regulating ocean carbonate chemistry and atmospheric CO 2 . Surprisingly, references to the absolute and relative contribution of these organisms to calcium carbonate production are lacking. Here we report quantification of pelagic calcium carbonate produc- tion in the North Pacific, providing new insights on the contribution of the three main planktonic calcifying groups. Our results show that coccolitho- phores dominate the living calcium carbonate (CaCO 3 ) standing stock, with coccolithophore calcite comprising ~90% of total CaCO 3 production, and pteropods and foraminifera playing a secondary role. We show that pelagic CaCO 3 production is higher than the sinking flux of CaCO 3 at 150 and 200 m at ocean stations ALOHA and PAPA, implying that a large portion of pelagic calcium carbonate is remineralised within the photic zone; this extensive shallow dissolution explains the apparent discrepancy between previous estimates of CaCO 3 production derived from satellite observations/biogeo- chemical modeling versus estimates from shallow sediment traps. We suggest future changes in the CaCO 3 cycle and its impact on atmospheric CO 2 will largely depend on how the poorly-understood processes that determine whether CaCO 3 is remineralised in the photic zone or exported to depth respond to anthropogenic warming and acidification

Bayesian Parameter Estimation for Latent Markov Random Fields and Social Networks

Undirected graphical models are widely used in statistics, physics and machine vision. However Bayesian parameter estimation for undirected models is extremely challenging, since evaluation of the posterior typically involves the calculation of an intractable normalising constant. This problem has received much attention, but very little of this has focussed on the important practical case where the data consists of noisy or incomplete observations of the underlying hidden structure. This paper specifically addresses this problem, comparing two alternative methodologies. In the first of these approaches particle Markov chain Monte Carlo (Andrieu et al., 2010) is used to efficiently explore the parameter space, combined with the exchange algorithm (Murray et al., 2006) for avoiding the calculation of the intractable normalising constant (a proof showing that this combination targets the correct distribution in found in a supplementary appendix online). This approach is compared with approximate Bayesian computation (Pritchard et al., 1999). Applications to estimating the parameters of Ising models and exponential random graphs from noisy data are presented. Each algorithm used in the paper targets an approximation to the true posterior due to the use of MCMC to simulate from the latent graphical model, in lieu of being able to do this exactly in general. The supplementary appendix also describes the nature of the resulting approximation.Comment: 26 pages, 2 figures, accepted in Journal of Computational and Graphical Statistics (http://www.amstat.org/publications/jcgs.cfm

Letter Ruling 99-1: Electronic Retailers

The synthesis and characterization of a set of redox-active iron and ruthenium alkynyl complexes of general formula [[M]­Cl_{(1–<i>p</i>)}{CCC₆H_5–<i>m</i>(CCFlu)_<i>m</i>}_(1+<i>p</i>)]­[PF₆]_<i>n</i> are reported (<i>n</i> = 0–1; <i>m</i> = 1–2; [M] = [Fe­(η⁵-C₅Me₅)­(κ²-dppe)] and <i>p</i> = 1 or [M] = [<i>trans</i>-Ru­(κ²-dppe)₂] and <i>p</i> = 0–1). The linear and third-order nonlinear optical properties of these new organometallic complexes featuring phenylalkynyl ligands functionalized by 2-fluorenyl (Flu) groups were studied in their stable redox states. Their first electronic transitions are assigned with the help of DFT calculations. We show here that these compounds possess significant third-order NLO responses in the near-IR range for molecules of their size. In particular, the remarkably large 2PA activities of the new Ru­(II) compounds in the 600–800 nm range (<i>Z</i>-scan) make them attractive nonlinear chromophores. Structure–property studies emphasize the importance of para- versus meta-connection of the 2-fluorenylethynyl units on the phenylalkynyl core and reveal that upon progressing from mono- to bis-alkynyl complexes a further increase of the 2PA cross section can be obtained while maintaining linear transparency in the visible range

Bayesian model comparison with un-normalised likelihoods

Models for which the likelihood function can be evaluated only up to a parameter-dependent unknown normalizing constant, such as Markov random field models, are used widely in computer science, statistical physics, spatial statistics, and network analysis. However, Bayesian analysis of these models using standard Monte Carlo methods is not possible due to the intractability of their likelihood functions. Several methods that permit exact, or close to exact, simulation from the posterior distribution have recently been developed. However, estimating the evidence and Bayes’ factors for these models remains challenging in general. This paper describes new random weight importance sampling and sequential Monte Carlo methods for estimating BFs that use simulation to circumvent the evaluation of the intractable likelihood, and compares them to existing methods. In some cases we observe an advantage in the use of biased weight estimates. An initial investigation into the theoretical and empirical properties of this class of methods is presented. Some support for the use of biased estimates is presented, but we advocate caution in the use of such estimates

Linear and Third-Order Nonlinear Optical Properties of Fe(n5-C5Me5)(k2-dppe)- and trans-Ru(k2-dppe)2-Alkynyl Complexes Containing 2-Fluorenyl End Groups

The synthesis and characterization of a set of redox-active iron and ruthenium alkynyl complexes of general formula [[M]Cl(1–p){C≡CC6H5–m(C≡CFlu)m}(1+p)][PF6]n are reported (n = 0–1; m = 1–2; [M] = [Fe(η5-C5Me5)(κ2-dppe)] and p = 1 or [M] = [trans-Ru(κ2-dppe)2] and p = 0–1). The linear and third-order nonlinear optical properties of these new organometallic complexes featuring phenylalkynyl ligands functionalized by 2-fluorenyl (Flu) groups were studied in their stable redox states. Their first electronic transitions are assigned with the help of DFT calculations. We show here that these compounds possess significant third-order NLO responses in the near-IR range for molecules of their size. In particular, the remarkably large 2PA activities of the new Ru(II) compounds in the 600–800 nm range (Z-scan) make them attractive nonlinear chromophores. Structure–property studies emphasize the importance of para- versus meta-connection of the 2-fluorenylethynyl units on the phenylalkynyl core and reveal that upon progressing from mono- to bis-alkynyl complexes a further increase of the 2PA cross section can be obtained while maintaining linear transparency in the visible range

A framework for parameter estimation and model selection from experimental data in systems biology using approximate Bayesian computation.

As modeling becomes a more widespread practice in the life sciences and biomedical sciences, researchers need reliable tools to calibrate models against ever more complex and detailed data. Here we present an approximate Bayesian computation (ABC) framework and software environment, ABC-SysBio, which is a Python package that runs on Linux and Mac OS X systems and that enables parameter estimation and model selection in the Bayesian formalism by using sequential Monte Carlo (SMC) approaches. We outline the underlying rationale, discuss the computational and practical issues and provide detailed guidance as to how the important tasks of parameter inference and model selection can be performed in practice. Unlike other available packages, ABC-SysBio is highly suited for investigating, in particular, the challenging problem of fitting stochastic models to data. In order to demonstrate the use of ABC-SysBio, in this protocol we postulate the existence of an imaginary reaction network composed of seven interrelated biological reactions (involving a specific mRNA, the protein it encodes and a post-translationally modified version of the protein), a network that is defined by two files containing 'observed' data that we provide as supplementary information. In the first part of the PROCEDURE, ABC-SysBio is used to infer the parameters of this system, whereas in the second part we use ABC-SysBio's relevant functionality to discriminate between two different reaction network models, one of them being the 'true' one. Although computationally expensive, the additional insights gained in the Bayesian formalism more than make up for this cost, especially in complex problems

Increasing Costs Due to Ocean Acidification Drives Phytoplankton to Be More Heavily Calcified: Optimal Growth Strategy of Coccolithophores

Ocean acidification is potentially one of the greatest threats to marine ecosystems and global carbon cycling. Amongst calcifying organisms, coccolithophores have received special attention because their calcite precipitation plays a significant role in alkalinity flux to the deep ocean (i.e., inorganic carbon pump). Currently, empirical effort is devoted to evaluating the plastic responses to acidification, but evolutionary considerations are missing from this approach. We thus constructed an optimality model to evaluate the evolutionary response of coccolithophorid life history, assuming that their exoskeleton (coccolith) serves to reduce the instantaneous mortality rates. Our model predicted that natural selection favors constructing more heavily calcified exoskeleton in response to increased acidification-driven costs. This counter-intuitive response occurs because the fitness benefit of choosing a better-defended, slower growth strategy in more acidic conditions, outweighs that of accelerating the cell cycle, as this occurs by producing less calcified exoskeleton. Contrary to the widely held belief, the evolutionarily optimized population can precipitate larger amounts of CaCO3 during the bloom in more acidified seawater, depending on parameter values. These findings suggest that ocean acidification may enhance the calcification rates of marine organisms as an adaptive response, possibly accompanied by higher carbon fixation ability. Our theory also provides a compelling explanation for the multispecific fossil time-series record from ∼200 years ago to present, in which mean coccolith size has increased along with rising atmospheric CO2 concentration

Bayesian Computation with Intractable Likelihoods

This article surveys computational methods for posterior inference with intractable likelihoods, that is where the likelihood function is unavailable in closed form, or where evaluation of the likelihood is infeasible. We review recent developments in pseudo-marginal methods, approximate Bayesian computation (ABC), the exchange algorithm, thermodynamic integration, and composite likelihood, paying particular attention to advancements in scalability for large datasets. We also mention R and MATLAB source code for implementations of these algorithms, where they are available.Comment: arXiv admin note: text overlap with arXiv:1503.0806

Coccolithophore ecology in the tropical and subtropical Atlantic Ocean: New perspectives from the Atlantic Meridional Transect (AMT) programme

Coccolithophore species composition was determined in 199 samples collected from the upper 300 m of the Atlantic Ocean, spanning temperate, tropical and subtropical waters in both hemispheres during four Atlantic Meridional Transect (AMT) cruises over the period 2003 to 2005. Of the 171 taxa observed, 140 consistently represented less than 5% of total cell numbers, and were classed as rare. Multivariate statistical techniques were used on the common taxa to assess variability in community composition vertically in the water column, horizontally across hydrographic provinces (subtropical gyres, equatorial waters, temperate waters), and temporally between cruises. Sharper gradients of statistical dissimilarity in species composition occurred vertically over a few tens of metres than horizontally over hundreds of kilometres. Three floral groups were identified from analysis of the depth of normalised abundance maxima in the subtropical gyres and equatorial waters: the upper euphotic zone (UEZ, >10% surface irradiance); the lower euphotic zone (LEZ, 10-1% surface irradiance); and the sub-euphotic zone (SEZ, <1% surface irradiance). The LEZ includes the deep chlorophyll maximum (DCM) and nutricline, and was characterised by species such as Emiliania huxleyi and Gephyrocapsa ericsonii which were also abundant at higher latitudes. It is suggested that this pattern reflects similarities in the light (and inorganic nutrient) conditions between the LEZ and temperate waters. The SEZ is below the depth where light is thought to be sufficient to support photosynthesis, suggesting that deep-dwelling species such as Florisphaera profunda and Gladiolithus spp. may be mixotrophic or phagotrophic, although conclusive proof will need to be gained experimentally. Mixotrophy could also be an important nutritional strategy for species abundant (Umbellosphaera spp., holococcolithophores) in the UEZ where inorganic nutrient concentrations are depleted and limiting to growth, although other nutritional strategies, such as the use of organic nutrients, are also possible. Statistical differences were also found in the species composition between the different cruises, with high levels of similarity for similar timed cruises (May or September-October). Few individual taxa showed significant variability in abundance over the time-span of sampling, except species such as E. huxleyi and G. ericsonii at higher latitudes. In subtropical and equatorial waters, high levels of species richness and low levels of species dominance remained throughout the sampling period indicating that seasonal fluctuations reflected differences in the whole coccolithophore community rather than in just one or a few species. Multivariate analyses of the taxa classified as rare also indicated some level of temporal, as well as vertical, zonation. Such insights into coccolithophore ecology and community composition provide important new perspectives that require innovative research to fully understand their impact on ocean biogeochemistry